Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context
The process of moving from experimental data to modeling and characterizing the dynamics and interactions in natural processes is a challenging task. This paper proposes an interactive platform for fitting data derived from experiments to mathematical expressions and carrying out spatial visualizati...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/13/4/104 |
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| author | Ritter A. Guimapi Samira A. Mohamed Lisa Biber-Freudenberger Waweru Mwangi Sunday Ekesi Christian Borgemeister Henri E. Z. Tonnang |
| author_facet | Ritter A. Guimapi Samira A. Mohamed Lisa Biber-Freudenberger Waweru Mwangi Sunday Ekesi Christian Borgemeister Henri E. Z. Tonnang |
| author_sort | Ritter A. Guimapi |
| collection | DOAJ |
| description | The process of moving from experimental data to modeling and characterizing the dynamics and interactions in natural processes is a challenging task. This paper proposes an interactive platform for fitting data derived from experiments to mathematical expressions and carrying out spatial visualization. The platform is designed using a component-based software architectural approach, implemented in R and the Java programming languages. It uses experimental data as input for model fitting, then applies the obtained model at the landscape level via a spatial temperature grid data to yield regional and continental maps. Different modules and functionalities of the tool are presented with a case study, in which the tool is used to establish a temperature-dependent virulence model and map the potential zone of efficacy of a fungal-based biopesticide. The decision support system (DSS) was developed in generic form, and it can be used by anyone interested in fitting mathematical equations to experimental data collected following the described protocol and, depending on the type of investigation, it offers the possibility of projecting the model at the landscape level. |
| first_indexed | 2024-03-10T20:15:11Z |
| format | Article |
| id | doaj.art-2c7ce0856fb3435f9d69790d61513636 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T20:15:11Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-2c7ce0856fb3435f9d69790d615136362023-11-19T22:34:19ZengMDPI AGAlgorithms1999-48932020-04-0113410410.3390/a13040104Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control ContextRitter A. Guimapi0Samira A. Mohamed1Lisa Biber-Freudenberger2Waweru Mwangi3Sunday Ekesi4Christian Borgemeister5Henri E. Z. Tonnang6International Centre of Insect Physiology and Ecology (ICIPE), Nairobi P.O. Box 30772-00100, KenyaInternational Centre of Insect Physiology and Ecology (ICIPE), Nairobi P.O. Box 30772-00100, KenyaCenter for Development Research (ZEF), Department of Ecology and Natural Resources Management, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyDepartment of Computing, School of Computing & Information Technology, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi P.O. Box 62000-00200, KenyaInternational Centre of Insect Physiology and Ecology (ICIPE), Nairobi P.O. Box 30772-00100, KenyaCenter for Development Research (ZEF), Department of Ecology and Natural Resources Management, University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyInternational Centre of Insect Physiology and Ecology (ICIPE), Nairobi P.O. Box 30772-00100, KenyaThe process of moving from experimental data to modeling and characterizing the dynamics and interactions in natural processes is a challenging task. This paper proposes an interactive platform for fitting data derived from experiments to mathematical expressions and carrying out spatial visualization. The platform is designed using a component-based software architectural approach, implemented in R and the Java programming languages. It uses experimental data as input for model fitting, then applies the obtained model at the landscape level via a spatial temperature grid data to yield regional and continental maps. Different modules and functionalities of the tool are presented with a case study, in which the tool is used to establish a temperature-dependent virulence model and map the potential zone of efficacy of a fungal-based biopesticide. The decision support system (DSS) was developed in generic form, and it can be used by anyone interested in fitting mathematical equations to experimental data collected following the described protocol and, depending on the type of investigation, it offers the possibility of projecting the model at the landscape level.https://www.mdpi.com/1999-4893/13/4/104Nonlinear regressioninteractive platformcomponent-based approachsoftware architectureEclipse-RCP (Rich Client Platform)spatial prediction |
| spellingShingle | Ritter A. Guimapi Samira A. Mohamed Lisa Biber-Freudenberger Waweru Mwangi Sunday Ekesi Christian Borgemeister Henri E. Z. Tonnang Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context Algorithms Nonlinear regression interactive platform component-based approach software architecture Eclipse-RCP (Rich Client Platform) spatial prediction |
| title | Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context |
| title_full | Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context |
| title_fullStr | Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context |
| title_full_unstemmed | Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context |
| title_short | Decision Support System for Fitting and Mapping Nonlinear Functions with Application to Insect Pest Management in the Biological Control Context |
| title_sort | decision support system for fitting and mapping nonlinear functions with application to insect pest management in the biological control context |
| topic | Nonlinear regression interactive platform component-based approach software architecture Eclipse-RCP (Rich Client Platform) spatial prediction |
| url | https://www.mdpi.com/1999-4893/13/4/104 |
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